# frbs v3.1-0

Monthly downloads

## Fuzzy Rule-Based Systems for Classification and Regression Tasks

An implementation of various learning algorithms based on fuzzy rule-based systems (FRBSs) for dealing with classification and regression tasks. Moreover, it allows to construct an FRBS model defined by human experts.
FRBSs are based on the concept of fuzzy sets, proposed by Zadeh in 1965, which aims at
representing the reasoning of human experts in a set of IF-THEN rules, to
handle real-life problems in, e.g., control, prediction and inference, data
mining, bioinformatics data processing, and robotics. FRBSs are also known
as fuzzy inference systems and fuzzy models. During the modeling of an
FRBS, there are two important steps that need to be conducted: structure
identification and parameter estimation. Nowadays, there exists a wide
variety of algorithms to generate fuzzy IF-THEN rules automatically from
numerical data, covering both steps. Approaches that have been used in the
past are, e.g., heuristic procedures, neuro-fuzzy techniques, clustering
methods, genetic algorithms, squares methods, etc. Furthermore, in this
version we provide a universal framework named 'frbsPMML', which is adopted
from the Predictive Model Markup Language (PMML), for representing FRBS
models. PMML is an XML-based language to provide a standard for describing
models produced by data mining and machine learning algorithms. Therefore,
we are allowed to export and import an FRBS model to/from 'frbsPMML'.
Finally, this package aims to implement the most widely used standard
procedures, thus offering a standard package for FRBS modeling to the R
community.

## Functions in frbs

Name | Description | |

FRBCS.eng | FRBCS: prediction phase | |

frbsPMML | The frbsPMML generator | |

rulebase | The rule checking function | |

DM.update | FIR.DM updating function | |

ANFIS | ANFIS model building | |

FRBCS.CHI | FRBCS.CHI model building | |

GFS.GCCL | GFS.GCCL model building | |

denorm.data | The data de-normalization | |

GFS.LT.RS.test | GFS.LT.RS: The prediction phase | |

summary.frbs | The summary function for frbs objects | |

FIR.DM | FIR.DM model building | |

frbs.eng | The prediction phase | |

HGD.update | FS.HGD updating function | |

ANFIS.update | ANFIS updating function | |

defuzzifier | Defuzzifier to transform from linguistic terms to crisp values | |

data.gen3d | A data generator | |

predict.frbs | The frbs prediction stage | |

GFS.GCCL.eng | GFS.GCCL.test: The prediction phase | |

ECM | Evolving Clustering Method | |

FS.HGD | FS.HGD model building | |

GFS.Thrift | GFS.Thrift model building | |

GFS.FR.MOGUL | GFS.FR.MOGUL model building | |

frbs-package | Getting started with the frbs package | |

FRBCS.W | FRBCS.W model building | |

FH.GBML | FH.GBML model building | |

WM | WM model building | |

GFS.LT.RS | GFS.LT.RS model building | |

SLAVE.test | SLAVE.test: The prediction phase | |

inference | The process of fuzzy reasoning | |

GFS.FR.MOGUL.test | GFS.FR.MOGUL: The prediction phase | |

SBC | The subtractive clustering and fuzzy c-means (SBC) model building | |

read.frbsPMML | The frbsPMML reader | |

frbsObjectFactory | The object factory for frbs objects | |

fuzzifier | Transforming from crisp set into linguistic terms | |

SLAVE | SLAVE model building | |

frbsData | Data set of the package | |

frbs.gen | The frbs model generator | |

DENFIS | DENFIS model building | |

plotMF | The plotting function | |

norm.data | The data normalization | |

HyFIS | HyFIS model building | |

SBC.test | SBC prediction phase | |

GFS.Thrift.test | GFS.Thrift: The prediction phase | |

write.frbsPMML | The frbsPMML writer | |

DENFIS.eng | DENFIS prediction function | |

HyFIS.update | HyFIS updating function | |

frbs.learn | The frbs model building function | |

No Results! |

## Last month downloads

## Details

License | GPL (>= 2) | file LICENSE |

URL | http://sci2s.ugr.es/dicits/software/FRBS |

Date | 2013-02-26 |

NeedsCompilation | no |

Packaged | 2015-05-22 10:01:26 UTC; Lala |

Repository | CRAN |

Date/Publication | 2015-05-22 13:19:10 |

suggests | class , e1071 , XML |

Contributors | Christoph Bergmeir, José Benítez, Lala Riza, Francisco Herrera |

#### Include our badge in your README

```
[![Rdoc](http://www.rdocumentation.org/badges/version/frbs)](http://www.rdocumentation.org/packages/frbs)
```